In today's business world, large companies must store and keep track of millions of pieces of information and data, using systems for distributed database data and file access and retrieval. The pieces of data, typically stored in databases, include information related to personnel, payroll, taxes, finances, real estate holdings, computer and communications equipment, office equipment, business plans and public documents, as well as other categories of information.
A company receives pieces of data at different times. For example, some pieces of data may have been obtained recently, within the last few months, while other pieces of data may have been obtained several years ago. In addition, different pieces of data are received in different manners. For example, one piece of data can be obtained from a human source, while another piece of data can be obtained from an in-house database, while still another piece of data may be obtained from a third-party entity's database.
Because different pieces of data are obtained at different times, and from different sources, some pieces of data are more likely to be accurate than others. For example, in general, pieces of data obtained more recently will tend to have a higher likelihood of being accurate than pieces of data obtained a relatively longer time ago. This is because, in a dynamic environment, circumstances upon which the piece of data is based can change, and are more likely to change as more time elapses. Similarly, pieces of data obtained from one source can have a higher likelihood of being accurate than pieces of data obtained from another source. For example, a piece of data obtained from a local database that is automatically updated may have a higher likelihood of being accurate than a piece of data obtained from a remotely-located human source.
A typical large company stores, references, and relies upon millions of pieces of data, each with a different probability or likelihood of being accurate. It is difficult, however, for a company to understand, when relying on data, which pieces of data are more likely to be accurate, and which pieces of data are less likely to be accurate, and by how much.
Because many important business decisions rely upon an analysis of many pieces of data, the lack of knowledge regarding the accuracy of different pieces of data can affect the accuracy of strategic and business decisions.
For example, if a company is approached, during licensing negotiations, by a software vender that alleges that the company's employees in several countries have a total of 170,000 copies of a certain desktop software application, and the company believes that the actual number is only 120,000, the company is at a disadvantage if it cannot determine the accuracy of its data related to the number of copies of software. In addition, companies tend to spend large amounts of time and resources validating data which is already accurate.
Accordingly, there are certain deficiencies with the manner in which companies store and reference data. Therefore, a need exists for improved systems and methods for managing company assets and data.